


import argparse
import json
import logging
import os
import sys
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


__a 					=   [
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        '''text-classification''',
        '''language-modeling''',
        '''summarization''',
        '''token-classification''',
        '''question-answering''',
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
  import run_clm_flax
  import run_flax_glue
  import run_flax_ner
  import run_mlm_flax
  import run_qa
  import run_summarization_flax
  import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

__a 					=   logging.getLogger()




def       __lowercase						(    )     ->Optional[int]:







      """simple docstring"""

      lowercase      : Any        =		argparse.ArgumentParser()
      parser.add_argument('''-f'''  )
      lowercase      : Union[str, Any]        =		parser.parse_args()
      return args.f




def       __lowercase						(    _UpperCamelCase,     _UpperCamelCase="eval"  )     ->Any:







      """simple docstring"""

      lowercase      : Tuple        =		os.path.join(UpperCamelCase_,     f"""{split}_results.json"""  )
      if os.path.exists(UpperCamelCase_  ):
            with open(UpperCamelCase_,     '''r'''  ) as f:
                  return json.load(UpperCamelCase_  )
      raise ValueError(f"""can't find {path}"""  )


__a 					=   logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







class 					__SCREAMING_SNAKE_CASE (      snake_case__ ):


      def 							__lowerCamelCase      (				self		):
            lowercase      : Optional[int]        =		self.get_auto_remove_tmp_dir()
            lowercase      : Optional[Any]        =		f"""
            run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --eval_steps=2
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

            with patch.object(_UpperCAmelCase				,    '''argv'''				,    _UpperCAmelCase		):
                  run_flax_glue.main()
                  lowercase      : Tuple        =		get_results(_UpperCAmelCase		)
                  self.assertGreaterEqual(result['''eval_accuracy''']				,    0.75		)


      @slow
      def 							__lowerCamelCase      (				self		):
            lowercase      : Any        =		self.get_auto_remove_tmp_dir()
            lowercase      : List[Any]        =		f"""
            run_clm_flax.py
            --model_name_or_path distilgpt2
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --block_size 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

            with patch.object(_UpperCAmelCase				,    '''argv'''				,    _UpperCAmelCase		):
                  run_clm_flax.main()
                  lowercase      : Dict        =		get_results(_UpperCAmelCase		)
                  self.assertLess(result['''eval_perplexity''']				,    100		)


      @slow
      def 							__lowerCamelCase      (				self		):
            lowercase      : List[str]        =		self.get_auto_remove_tmp_dir()
            lowercase      : Any        =		f"""
            run_summarization.py
            --model_name_or_path t5-small
            --train_file tests/fixtures/tests_samples/xsum/sample.json
            --validation_file tests/fixtures/tests_samples/xsum/sample.json
            --test_file tests/fixtures/tests_samples/xsum/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=8
            --do_train
            --do_eval
            --do_predict
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --predict_with_generate
        """.split()

            with patch.object(_UpperCAmelCase				,    '''argv'''				,    _UpperCAmelCase		):
                  run_summarization_flax.main()
                  lowercase      : List[str]        =		get_results(_UpperCAmelCase				,    split='''test'''		)
                  self.assertGreaterEqual(result['''test_rouge1''']				,    10		)
                  self.assertGreaterEqual(result['''test_rouge2''']				,    2		)
                  self.assertGreaterEqual(result['''test_rougeL''']				,    7		)
                  self.assertGreaterEqual(result['''test_rougeLsum''']				,    7		)


      @slow
      def 							__lowerCamelCase      (				self		):
            lowercase      : Optional[int]        =		self.get_auto_remove_tmp_dir()
            lowercase      : List[Any]        =		f"""
            run_mlm.py
            --model_name_or_path distilroberta-base
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --logging_steps 2 --eval_steps 2
            --do_train
            --do_eval
            --num_train_epochs=1
        """.split()

            with patch.object(_UpperCAmelCase				,    '''argv'''				,    _UpperCAmelCase		):
                  run_mlm_flax.main()
                  lowercase      : Optional[Any]        =		get_results(_UpperCAmelCase		)
                  self.assertLess(result['''eval_perplexity''']				,    42		)


      @slow
      def 							__lowerCamelCase      (				self		):
            lowercase      : str        =		self.get_auto_remove_tmp_dir()
            lowercase      : Optional[Any]        =		f"""
            run_t5_mlm_flax.py
            --model_name_or_path t5-small
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

            with patch.object(_UpperCAmelCase				,    '''argv'''				,    _UpperCAmelCase		):
                  run_ta_mlm_flax.main()
                  lowercase      : int        =		get_results(_UpperCAmelCase		)
                  self.assertGreaterEqual(result['''eval_accuracy''']				,    0.42		)


      @slow
      def 							__lowerCamelCase      (				self		):
            # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
            lowercase      : Any        =		7 if get_gpu_count() > 1 else 2

            lowercase      : Optional[Any]        =		self.get_auto_remove_tmp_dir()
            lowercase      : str        =		f"""
            run_flax_ner.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/conll/sample.json
            --validation_file tests/fixtures/tests_samples/conll/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --warmup_steps=2
            --learning_rate=2e-4
            --logging_steps 2 --eval_steps 2
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=2
            --num_train_epochs={epochs}
            --seed 7
        """.split()

            with patch.object(_UpperCAmelCase				,    '''argv'''				,    _UpperCAmelCase		):
                  run_flax_ner.main()
                  lowercase      : str        =		get_results(_UpperCAmelCase		)
                  self.assertGreaterEqual(result['''eval_accuracy''']				,    0.75		)
                  self.assertGreaterEqual(result['''eval_f1''']				,    0.3		)






      @slow
      def 							__lowerCamelCase      (				self		):
            lowercase      : Union[str, Any]        =		self.get_auto_remove_tmp_dir()
            lowercase      : List[str]        =		f"""
            run_qa.py
            --model_name_or_path bert-base-uncased
            --version_2_with_negative
            --train_file tests/fixtures/tests_samples/SQUAD/sample.json
            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=2
            --do_train
            --do_eval
            --logging_steps 2 --eval_steps 2
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        """.split()

            with patch.object(_UpperCAmelCase				,    '''argv'''				,    _UpperCAmelCase		):
                  run_qa.main()
                  lowercase      : int        =		get_results(_UpperCAmelCase		)
                  self.assertGreaterEqual(result['''eval_f1''']				,    30		)
                  self.assertGreaterEqual(result['''eval_exact''']				,    30		)






'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import _LazyModule


SCREAMING_SNAKE_CASE__     :						Dict	=  {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}


if TYPE_CHECKING:
			from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
			import sys

			SCREAMING_SNAKE_CASE__     :						Dict	=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




